Computer
Farah Tawfiq Abdul Hussien; Abdul Monem S. Rahma; Hala Bahjat Abdul Wahab
Abstract
Providing security for each online consumer over the internet is a critical issue that may cause a time consuming problem that may cause big load on the website server especially for the large websites at the rush time. This process may generate a variety of issues, including response time delays, client ...
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Providing security for each online consumer over the internet is a critical issue that may cause a time consuming problem that may cause big load on the website server especially for the large websites at the rush time. This process may generate a variety of issues, including response time delays, client orders being lost, and system crash or deadlock, all of which decrease system performance. This work intends to present a new multi-agent system prototype structure that solves the challenge of security while avoiding issues that might degrade system performance. This is accomplished by installing a software agent on the client's device that handles the purchase and encryption processes without the need for the user to intervene. The suggested agent evades the problems of stalemate (i.e., failure) and request loss, ensuring that information exchanged between all entities is protected. The use of a software agent to manage buying and encrypting operations improves system performance by 10% and increases the reaction time of the system by 30.5 percent (response time, page loading time, transaction processing speed, orders per second) according to test results.
Computer
Hayder I. Mutar; Muna M. Jawad
Abstract
Wireless Sensor Networks (WSNs) have become the most cost- effective monitoring solution due to their low cost, despite their major drawback of limited power due to dependence on batteries. Each Sensor Node (SN) is clustered in a particular location and forms a network by self-organizing. They often ...
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Wireless Sensor Networks (WSNs) have become the most cost- effective monitoring solution due to their low cost, despite their major drawback of limited power due to dependence on batteries. Each Sensor Node (SN) is clustered in a particular location and forms a network by self-organizing. They often operate in some of the world's most unusual or dangerous conditions. Networking errors, memory and processor limitations, and energy constraints all pose problems for WSN developers. Many problems in WSNs are expressed as multivariate optimization problems that are solved using biologically inspired techniques. Particle swarm optimization (PSO) is an easy, algorithmically sound, and robust optimization technique. It has been used to address problems like Clustering, data routing, Cluster Head (CH) collection, and data collecting in WSNs. This paper presents a brief analysis of WSN studies in which the PSO algorithm was used as the primary or secondary algorithm for enhancing lifespan of WSNs, focusing on results that show energy efficiency in the sensors, extending the network's life.
Computer
Zeina Abdullah Humadi; Qusay Fadhel Al-Doori
Abstract
Communication and computing systems have made it easier for the world to transfer data and information from the sender to the recipient at the lowest cost and most efficiency. The transmission process may cause data corruption or error for many reasons, including the environment, the large volume of ...
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Communication and computing systems have made it easier for the world to transfer data and information from the sender to the recipient at the lowest cost and most efficiency. The transmission process may cause data corruption or error for many reasons, including the environment, the large volume of transmitted data, heat, and noise. for these Reasons, There is a need to correct and treat these errors. Individual errors can be easily corrected by hamming code, while burst errors cannot be corrected easily and need a hardware device called the interleaver used to correct the burst error. In this research, the different types of interleaver are studied and compared to find the best interleaver in order to increase the efficiency and accuracy of the systems. The issue is that interleaving takes a long time, which increases the turbo code's overall execution time. Our goal is to create an interleaver that is more sensitive and efficient than other varieties.
Control
Ruaa S. Hassan; Farazdaq R. Yaseen
Abstract
Permanent Magnet Synchronous Motors (PMSM) are extensively used in the industry owing to their excellent efficiency, low weight/power ratio, and smooth torque with no or minimal ripple. Field Oriented Control (FOC) is a modern and effective approach for closed-loop controlling the speed of PMSM. In this ...
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Permanent Magnet Synchronous Motors (PMSM) are extensively used in the industry owing to their excellent efficiency, low weight/power ratio, and smooth torque with no or minimal ripple. Field Oriented Control (FOC) is a modern and effective approach for closed-loop controlling the speed of PMSM. In this paper, three-level Space Vector Pulse Width Modulation (SVPWM) is proposed for minimizing harmonics in the output voltage inverter. sensorless approaches are performed by using Model Reference Adaptive System (MRAS) which eliminates mechanical uncertainties. Because mechanical sensors increase the cost, size, weight, and wiring complexity, employing PMSM with them is extremely difficult Tuning of Proportional Integral (PI) controller gains is performed by using the Whale Optimization Algorithm (WOA). The results show that the proposed controller enhances the system's performance. In the application of felid-oriented control to a PMSM, with simulation data to back it up the entire system is simulated using the MATLAB/Simulink tool.
Control
Bashar F. Midhat
Abstract
In most applications, electric drives are actuated using on/off devices due to their low cost and also due to the relatively high power consumption of the electric drives which make applying linear power amplifiers very costly. In this paper, the operation of PMDC motors under discontinuous control action ...
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In most applications, electric drives are actuated using on/off devices due to their low cost and also due to the relatively high power consumption of the electric drives which make applying linear power amplifiers very costly. In this paper, the operation of PMDC motors under discontinuous control action is analyzed. In addition, to reduce chattering, boundary layer solution has been addressed. Both suggested control techniques have been applied to a PMDC motor model in a software simulation using MATLAB. The results show better performance of boundary layer technique due to the reduced chattering.
Computer
Noor Abdul Khaleq Zghair; Ahmed S. Al-Araji
Abstract
A mobile robot's major purpose is to get to its destination by traveling over an optimum path defined by various parameters such as time, distance, and the robot's safety from any impediments in its path. As a result, the backbone of the autonomous mobile robot is path planning and obstacle avoidance. ...
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A mobile robot's major purpose is to get to its destination by traveling over an optimum path defined by various parameters such as time, distance, and the robot's safety from any impediments in its path. As a result, the backbone of the autonomous mobile robot is path planning and obstacle avoidance. Several algorithms for path planning and obstacle avoidance have been presented by various researchers, each with its own set of benefits and drawbacks. This paper focuses on two parts; the first part finds the short and smooth collision-free path for a mobile robot to navigate in a static environment based on two proposed hybrid algorithms. The first hybrid is between Firefly Algorithm (FA) and Modify Chaotic Particle Swarm Optimization (MCPSO), namely (HFACPSO), while the other hybrid is between Genetic Algorithm (GA) and MCPSO, namely (HGACPSO).The second part suggests an algorithm planner for improving the efficiency of the route-planning algorithm with moving obstacle avoidance by adjusting the velocity or re-planning the path for the mobile robot. To demonstrate the effectiveness of the proposed algorithms in terms of the shortest path length and collision-free, as well as obtaining optimal or near-optimal wheel velocities with the minimum number of iterations. The proposed hybrid (FAMCPSO) algorithm provides enhancement on the path length equal to (0.82%) compared to the firefly algorithm (FA). Moreover, the hybrid (GAMCPSO) algorithm enhancement on the path length equals (0.67%) compared to the genetic algorithm (GA). All methods are simulated in a static and dynamic obstacle environment using MATLAB 2018b.
Communication
Bushra T. Hashim; Hadi T. Ziboon; Sinan M. Abdulsatar
Abstract
A new technique called cognitive radio seeks to utilize the available spectrum.. Spectrum sensing is the fundamental cognitive radio component. There are many types of sensing spectrums, one of which is The Two Thresholds Based on Covariance Absolute Values (TTCAV) method. This method's confused region, ...
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A new technique called cognitive radio seeks to utilize the available spectrum.. Spectrum sensing is the fundamental cognitive radio component. There are many types of sensing spectrums, one of which is The Two Thresholds Based on Covariance Absolute Values (TTCAV) method. This method's confused region, which is unsure whether it is a signal or noise, is one of its drawbacks. To solve this problem proposed two techniques, a 2-bit quantization technique and a 3-bit quantization technique. Both techniques use an adaptive threshold. The experimental results conducted using python version 3.7 and Jetson Nano kit show an improvement in the detection probability values after using the techniques. where the value of 𝑷𝒅= 80.2% for a 2-bit technique, 𝑷𝒅=90.3% for a 3-bit quantization technique,at SNR=-20 under smoothing factor L=3. The Monte Carlo was used to determine the effectiveness of the proposed techniques, and Binary Phase Shift Keying modulation BPSK. According to the experiment, the results after using the proposed techniques are better than before.
Computer
Ekhlas Kadhum Hamza; Marwan Alaa Hussein
Abstract
As the Internet of Things (IoT) is growing in popularity globally, which has resulted in a rise in cyber threats, experts are focusing more on its security. The majority of IoT security research to date has concentrated on huge devices, while small IoT devices have received comparably little attention. ...
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As the Internet of Things (IoT) is growing in popularity globally, which has resulted in a rise in cyber threats, experts are focusing more on its security. The majority of IoT security research to date has concentrated on huge devices, while small IoT devices have received comparably little attention. Our primary purpose is, therefore, to research how to ensure the operation of IoT devices that are small. The security gateway is a Security Settings on the Gateway for RaspberryPi built gateway that may link Internet of Things devices to their private network, safeguarding IoT devices from exposure to external networks. In addition, a variety of Security Settings on the Gateway for RaspberryPi security settings are installed, including fiel2ban and a Security Settings on the Gateway for RaspberryPi firewall, in order to avoid brute force and dictionary attacks. This article also studies the communication between Internet of Things (IoT) devices utilizing various secure communications, including Secure Shell (SSH), and analyzes their performance in a variety of circumstances. The gateway's experimental evaluation reveals that the proposed framework can secure tiny IoT devices.
Computer
Raja’a M. Mohammed; Suhad M. Kadhem
Abstract
Sign language (SL) is Non-verbal communication and a way for thedeaf and mute to communicate without words. A deaf and mute person's hands,face, and body shows what they want to say. Since the number of deaf and dumbpeople is increasing, there must be other ways to learn sign language orcommunicate with ...
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Sign language (SL) is Non-verbal communication and a way for thedeaf and mute to communicate without words. A deaf and mute person's hands,face, and body shows what they want to say. Since the number of deaf and dumbpeople is increasing, there must be other ways to learn sign language orcommunicate with deaf and dumb people. One of these ways is using advancedtechnology to produce systems that help the deaf/dumb, such as creatingrecognition and sign language translators. This paper presents an applicationthat works on the computer for machine translation of Iraqi sign language intwo directions from sign language to Arabic language (text/speech) and fromArabic language(text) to Iraqi sign language. The proposed system uses aConvolution Neural Network (CNN) to classify sign language based on itsfeatures to predicate the sign meaning. The sign language to Arabiclanguage(text/speech) part of the proposed system has an accuracy of 99.3% forletters.
Control
Zahraa Ali Waheed; Amjad Jaleel Humaidi
Abstract
Physiotherapeutic exoskeleton devices have recently been developed to helppeople rehabilitate impaired limb mobility and replace the use of physiotherapists. Suchsystems are characterized by high nonlinear and time-varying coefficients. In order tocope with such difficult control challenges, a need arose ...
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Physiotherapeutic exoskeleton devices have recently been developed to helppeople rehabilitate impaired limb mobility and replace the use of physiotherapists. Suchsystems are characterized by high nonlinear and time-varying coefficients. In order tocope with such difficult control challenges, a need arose for reliable nonlinearcontrollers. While in this study the Sliding Mode Control (SMC) was used to track thetrajectory of the knee exoskeleton-system (KES) while having parameter uncertainty. Inaddition, the whale optimization algorithm (WOA) was introduced and developed toadjust the thickness design parameters for further optimization of its performance. Thesimulation was performed on a calculator using the MATLAB-Simulink program toconduct a comparative study between the optimal and Classical SMC where the resultsof comparison with the test parameters used by the SMC showed, the results of theproposed optimal SMC revealed that the positioning inaccuracy of the knee increased by31.8807% and it follows from this result that the controller could successfully performtracking the track well. Also, the control system created at the optimal thickness has abetter dynamic performance than the classical thickness.
Computer
Asmaa Hasan Alrubaie; Maisa'a Abid Ali Khodher; Ahmed Talib Abdulameer
Abstract
Target detection, one of the key functions of computer vision, has grown in importance as a study area over the past two decades and is currently often employed. In a certain video, it seeks to rapidly and precisely detect and locate a huge amount of the objects according to redetermined categories. ...
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Target detection, one of the key functions of computer vision, has grown in importance as a study area over the past two decades and is currently often employed. In a certain video, it seeks to rapidly and precisely detect and locate a huge amount of the objects according to redetermined categories. The two forms of deep learning (DL) algorithms that are used in the model training algorithm are single-stage and 2-stage algorithms of detection. The representative algorithms for every level have been thoroughly discussed in this work. The analysis and comparison of numerous representative algorithms in this subject is after that explained. Last but not least, potential obstacles to target detection are anticipated.
Computer
Suha Mohammed Saleh; Abdulamir A. Karim
Abstract
From big data analytics to computer vision and human-level control, deep learning has been effectively applied to a wide range of complicated challenges. However, these same deep learning advancements have also been used to develop malicious software that threatens individuals' personal data, democratic ...
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From big data analytics to computer vision and human-level control, deep learning has been effectively applied to a wide range of complicated challenges. However, these same deep learning advancements have also been used to develop malicious software that threatens individuals' personal data, democratic processes, and even national security. Apps backed by deep learning have lately appeared, with deepfake being one of the most notable. Deepfake algorithms can create fake images and videos that humans cannot distinguish them from authentic ones. One of the fields that deep learning accomplished major success is face synthesis and animation generation. On the other hand, it can create unethical software called deepfake that presents a severe privacy threat or even a huge security risk that can affect innocent people. This work introduces the most recent algorithms and methods used in deepfake. In addition, it provides a brief explanation of the principles that underpin these technologies and facilitates the development of this field by identifying the challenges and scopes that require further investigation in the future.
Computer
Talah Oday Alani; Ameer Mosa Al-Sadi
Abstract
Software-Defined Network (SDN) is one of the most predominant technologies for networking in the existing and next-generation networks. SDN can conFig. , control, protect, and optimize network resources through software. The fundamental benefit of SDN is enabling the application of dynamic management. ...
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Software-Defined Network (SDN) is one of the most predominant technologies for networking in the existing and next-generation networks. SDN can conFig. , control, protect, and optimize network resources through software. The fundamental benefit of SDN is enabling the application of dynamic management. In addition, the literature shows that partitioning a Software-Defined Wide Area Network (SD-WAN) into several logical networks efficiently will optimize its performance. The main aim of paper is to design an algorithm to slice SD-WAN dynamically into several virtual networks according to the server-clients’ correlation using the Virtual Local Area Network (VLAN). The several virtual networks improve QoS of SD-WAN and reduce its broadcasting domain. The proposed framework consists of two parts. The first part is the management algorithm that finds the best server for each client; then it groups this server with their client in a dedicated logical network. The second part includes creating a VLAN for each logical network in an SD-WAN. The application of the POX controller calculates and maintains the dynamic VLAN, which will be applied by the control plan to slice the topology in the data plan. SD-WAN topology is tested before and after applying VLANs. The results show enhancement in latency by 42.85%, throughput by 4.61%, loss packet by 72% and jitter by 47.86% after applying VLAN. Finally, the greatest gain is reducing the broadcasting ratio by 77.77%.
Computer
Huda M. Rada; Alia Karim Abdul Hassan; Ali H. Al-Timemy
Abstract
Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive ...
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Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that using mean absolute value (MAV), waveform length (WL), Wilson Amplitude (WAMP), Sine Slope Changes (SSC), and Cardinality features of the proposed algorithm achieves a classification accuracy of 89.6% when classifying seven distinct types of hand and wrist movement.
Computer
Lafta R. Al-Khazraji; Ayad R. Abbas; Abeer S. Jamil
Abstract
Deep Dream (DD) is a new technology that works as a creative image-editing approach by employing the representations of CNN to produce dreams-like images by taking the benefits of both Deep CNN and Inception to build the dream through layer-by-layer implementation. As the days go by, the DD becomes widely ...
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Deep Dream (DD) is a new technology that works as a creative image-editing approach by employing the representations of CNN to produce dreams-like images by taking the benefits of both Deep CNN and Inception to build the dream through layer-by-layer implementation. As the days go by, the DD becomes widely used in the artificial intelligence (AI) fields. This paper is the first systematic review of DD. We focused on the definition, importance, background, and applications of DD. Natural language processing (NLP), images, videos, and audio are the main fields in which DD is applied. We also discussed the main concepts of the DD, like transfer learning and Inception. We addressed the contributions, databases, and techniques that have been used to build the models, the limitations, and evaluation metrics for each one of the included research papers. Finally, some interesting recommendations have been listed to serve the researchers in the future.
Computer
Sabah Abdulazeez Jebur; Khalid A. Hussein; Haider Kadhim Hoomod
Abstract
The use of video surveillance systems has increased due to security concerns and their relatively low cost. Researchers are working to create intelligent Closed Circuit Television (CCTV) cameras that can automatically analyze behavior in real-time to detect anomalous behaviors and prevent dangerous accidents. ...
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The use of video surveillance systems has increased due to security concerns and their relatively low cost. Researchers are working to create intelligent Closed Circuit Television (CCTV) cameras that can automatically analyze behavior in real-time to detect anomalous behaviors and prevent dangerous accidents. Deep Learning (DL) approaches, particularly Convolutional Neural Networks (CNNs), have shown outstanding results in video analysis and anomaly detection. This research paper focused on using Inception-v3 transfer learning approaches to improve the accuracy and efficiency of abnormal behavior detection in video surveillance. The Inceptionv3 network is used to classify keyframes of a video as normal or abnormal behaviors by utilizing both pre-training and fine-tuning transfer learning approaches to extract features from the input data and develop a new classifier. The UCF-Crime dataset is used to train and evaluate the proposed models. The performance of both models was evaluated using accuracy, recall, precision, and F1 score. The fine-tuned model achieved 88.0%, 89.24%, 85.83%, and 87.50% for these measures, respectively. In contrast, the pre-trained model obtained 86.2%, 86.43%, 84.62%, and 85.52%, respectively. These results demonstrate that transfer learning using Inception-v3 architecture can effectively classify normal and abnormal behaviors in videos, and fine-tuning the weights of the layers can further improve the model's performance.
